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Joint Bayesian analysis of birthweight and censored gestational age using finite mixture models.

Publication ,  Journal Article
Schwartz, SL; Gelfand, AE; Miranda, ML
Published in: Statistics in medicine
July 2010

Birthweight and gestational age are closely related and represent important indicators of a healthy pregnancy. Customary modeling for birthweight is conditional on gestational age. However, joint modeling directly addresses the relationship between gestational age and birthweight, and provides increased flexibility and interpretation as well as a strategy to avoid using gestational age as an intermediate variable. Previous proposals have utilized finite mixtures of bivariate regression models to incorporate well-established risk factors into analysis (e.g. sex and birth order of the baby, maternal age, race, and tobacco use) while examining the non-Gaussian shape of the joint birthweight and gestational age distribution. We build on this approach by demonstrating the inferential (prognostic) benefits of joint modeling (e.g. investigation of 'age inappropriate' outcomes like small for gestational age) and hence re-emphasize the importance of capturing the non-Gaussian distributional shapes. We additionally extend current models through a latent specification which admits interval-censored gestational age. We work within a Bayesian framework which enables inference beyond customary parameter estimation and prediction as well as exact uncertainty assessment. The model is applied to a portion of the 2003-2006 North Carolina Detailed Birth Record data (n=336129) available through the Children's Environmental Health Initiative and is fitted using the Bayesian methodology and Markov chain Monte Carlo approaches.

Duke Scholars

Published In

Statistics in medicine

DOI

EISSN

1097-0258

ISSN

0277-6715

Publication Date

July 2010

Volume

29

Issue

16

Start / End Page

1710 / 1723

Related Subject Headings

  • Young Adult
  • Statistics & Probability
  • Statistical Distributions
  • Smoking
  • Regression Analysis
  • Racial Groups
  • Premature Birth
  • Pregnancy
  • North Carolina
  • Monte Carlo Method
 

Citation

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ICMJE
MLA
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Schwartz, S. L., Gelfand, A. E., & Miranda, M. L. (2010). Joint Bayesian analysis of birthweight and censored gestational age using finite mixture models. Statistics in Medicine, 29(16), 1710–1723. https://doi.org/10.1002/sim.3900
Schwartz, Scott L., Alan E. Gelfand, and Marie L. Miranda. “Joint Bayesian analysis of birthweight and censored gestational age using finite mixture models.Statistics in Medicine 29, no. 16 (July 2010): 1710–23. https://doi.org/10.1002/sim.3900.
Schwartz SL, Gelfand AE, Miranda ML. Joint Bayesian analysis of birthweight and censored gestational age using finite mixture models. Statistics in medicine. 2010 Jul;29(16):1710–23.
Schwartz, Scott L., et al. “Joint Bayesian analysis of birthweight and censored gestational age using finite mixture models.Statistics in Medicine, vol. 29, no. 16, July 2010, pp. 1710–23. Epmc, doi:10.1002/sim.3900.
Schwartz SL, Gelfand AE, Miranda ML. Joint Bayesian analysis of birthweight and censored gestational age using finite mixture models. Statistics in medicine. 2010 Jul;29(16):1710–1723.
Journal cover image

Published In

Statistics in medicine

DOI

EISSN

1097-0258

ISSN

0277-6715

Publication Date

July 2010

Volume

29

Issue

16

Start / End Page

1710 / 1723

Related Subject Headings

  • Young Adult
  • Statistics & Probability
  • Statistical Distributions
  • Smoking
  • Regression Analysis
  • Racial Groups
  • Premature Birth
  • Pregnancy
  • North Carolina
  • Monte Carlo Method